Hi Matthew,

As you note, Skyline can't generate an isotope distribution without knowing the chemical makeup of the precursor. So there's nothing Skyline can do with those full scan settings absent a formula.

One way to approach this manually is to embed the isotope mass offsets in a series of precursor adduct descriptions in your transition list - this would get you the m/z values of interest though they'd be understood as labels rather than natural isotopes (so, still no idotp, but you would see chromatograms). You can read up on that at https://skyline.ms/wiki/home/software/Skyline/page.view?name=adduct_descriptions ("Charge-Only Examples with Isotope Labels Described Only by Mass").

Importing isotope distribution values if you somehow know them might be something that could be implemented - can you provide a transition list that somehow imparts that information? I wonder, though, how you know the isotope distribution without knowing the chemical formula?

Thanks for using the Skyline support board!

Brian Pratt

Hi Brian

Thanks for this. I've managed to manually add precursors to the molecules by pretending they are deuterated: [MD+], [MD+H],[M2D+]. I guess it's bit of a hack but it works.

I have a few thoguhts on your question to me. It's unlikley to be a priority but it's interesting.

I don't think I could ever know the isotope distribution paturn without knowing the chemical formula. I'm using skyline to quantify features identified in the mass spec data that are thought to be descriminatory prior to identifiction, and using skyline to match the features across many files. So for my use case I guess the following features would be helpful.

The simplest would be If I could ask skyline to pick the members of the isotope envelope based on peak separations computed from the charge of the precurser and a reasonable average of the mass of neucleotides in organic molecules, which is very nearly 1/z.

A more sophisticated version of the above might be to let me enter a stociometric statement of the the dominant atoms in the molecule and have skyline calculate the isotope distribution for a molecule with such a composition of nearest mass to each analyte, then shift the isotope distribution to match the first precurser's m/z. That wouldn't make sense in all cases. In mine, I'm looking at fatty acid chains, there will be various adducts, double bonds, and heteroatoms, but an isotope distribution scaled derived from a molecule CnH2n with the closest matching m/z wouldn't be very wrong.

Then I guess for matching features across files, one posibility would be to define one file as the master file, and calculate the dot product for the isotope envelope in subsequent files against that first file. In a similar way to retention time being predicted on the basis of a chosen file.

Interesting - we're wandering into feature finding territory. We've recently integrated Hardklor, which is a tool for finding peptide-like features - where "peptide-like" is based on an averagine model. We're now thinking about other models suitable for other kinds of molecules, which I think is pretty much what you're describing.

One tweak we made to Hardklor is to have it pass the chemical formula it used in determining the isotope envelope for a feature, which allows Skyline to perform idotp calculations and so forth.

Though it sounds like you already have some kind of feature finding tool - may I ask what you're using? We're also interested in possibly integrating other tools rather than further tweaking Hardklor.

Best regards,

Brian

Dear Nick

So I tried the approach you described. I used R and a package that calculates a molecular formula called mass tools currently available on github.

I've been able to build transition lists with pseudo molecular formula and the mass modification you described. The isotope dot products are around 0.97 which is a fairly good agreement.

I've put the code I used to generate the formula with mass modification below in case it is useful to someone. In practice that piece of code sits in a loop in my R function and sequentially generates a molecular formula with modification for each feature.

install.packages("remotes")
remotes::install_github("mjhelf/MassTools")
library(MassTools)

### Find Molecular Formula 

# In practice the mz below is set to that of each ion in turn using a loop.
formCal<-calcMF(mz=200.000659,
			elements = Rdisop::initializeCHNOPS()[1:4],
			summarize = FALSE,
			top=1)

if(! is.null(formCal)){

molecForm<-
paste(formCal[['MF']],"[",
			ifelse(sign(formCal[['error']])<=0,"+","-"),
			as.character(abs(round(formCal[['error']],6))),"]",sep="")

print(molecForm)

}else{

	molecForm<-""

}